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A two-stage shape retrieval (TSR) method with global and local features

机译:具有全局和局部特征的两阶段形状检索(TSR)方法

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摘要

A robust two-stage shape retrieval (TSR) method is proposed to address the 2D shape retrieval problem. Most state-of-the-art shape retrieval methods are based on local features matching and ranking. Their retrieval performance is not robust since they may retrieve globally dissimilar shapes in high ranks. To overcome this challenge, we decompose the decision process into two stages. In the first irrelevant cluster filtering (ICF) stage, we consider both global and local features and use them to predict the relevance of gallery shapes with respect to the query. Irrelevant shapes are removed from the candidate shape set. After that, a local-features-based matching and ranking (LMR) method follows in the second stage. We apply the proposed TSR system to MPEG-7, Kimia99 and Taril 000 three datasets and show that it outperforms all other existing methods. The robust retrieval performance of the TSR system is demonstrated. (C) 2016 Elsevier Inc. All rights reserved.
机译:提出了一种鲁棒的两阶段形状检索(TSR)方法来解决二维形状检索问题。大多数最新的形状检索方法都是基于局部特征匹配和排序。它们的检索性能不强健,因为它们可能会在高等级中检索全局不同的形状。为了克服这一挑战,我们将决策过程分为两个阶段。在第一个不相关的聚类过滤(ICF)阶段,我们考虑全局和局部特征,并使用它们来预测画廊形状与查询的相关性。从候选形状集中删除无关的形状。之后,第二阶段将采用基于局部功能的匹配和排名(LMR)方法。我们将建议的TSR系统应用于MPEG-7,Kimia99和Taril 000三个数据集,并证明它优于所有其他现有方法。展示了TSR系统的强大检索性能。 (C)2016 Elsevier Inc.保留所有权利。

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